NBA Early-Career Competition Analysis
Objective
Examine how rookie- and sophomore-year positional competition affects NBA lottery picks’ scoring trajectories over their first five seasons. Positional competition measures how crowded a player’s role is on their team.
Main Findings
★ After accounting for individual and team-level factors, players facing higher sophomore-year competition start strong, then plateau or even decline in points per game over time, while rookie-year competition slightly boosts baseline scoring without affecting growth.
Methods
Data: Player stats from Basketball Reference, cleaned and processed in Python and R.
Model: Linear mixed-effects model capturing player-level differences over time.
Validation: Confidence intervals and diagnostics ensured reliable estimates.
Visualization: Interactive plots of predicted scoring trajectories.
Why It Matters
The methods used here can be applied beyond sports analytics, in areas such as:
Finance: Modeling portfolio growth under varying conditions.
Healthcare: Tracking patient outcomes over time under different treatments.
Education: Evaluating student performance trajectories across learning environments.
Deep Dive
The full analysis including data processing, model building, and detailed results is available: